IIT at TREC-8: Improving Baseline Precision
نویسندگان
چکیده
In TREC-8, we participated in the automatic and manual tracks for category A as well as the small web track. This year, we focussed on improving our baseline and then introduced some experimental improvements. Our automatic runs used relevance feedback with a high-precision first pass to select terms and then a high-recall final pass. For manual runs, we used predefined concept lists focussing on phrases and proper nouns in the query. In the small web-track, we submitted one content-only run and two link-plus-content runs. We continued to use the relational model with unchanged SQL for retrieval. Our results show some promise for the use of automatic concepts, expansion within concepts and a high-precision first pass for relevance feedback.
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IIT at TREC-8: Improved Manual Query Processing and Using Stemming Equivalence Classes as a Basis for Relevance Feedback
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